Abstract
Ever since gender issues entered into the domain of policy analysis, efforts have been made to monitor the progress of interventions through two major indices suggested by UNDP, viz., the gender-related development index (GDI) and the gender empowerment measure (GEM).
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Notes
- 1.
In spite of extensive controversy in the literature related to the suitability of defining capability in terms of any observable achievement indicator, we are proposing a measurement of empowerment in terms of capability enhancement as our purpose is primarily lying in developing and illustrating a methodology where a latent variable can be measured as a function of another latent variable along with a bunch of other observable indicators.
- 2.
Even if achieved functionings have been considered in a non-aggregative fashion, their contribution in constituting the latent capability leaves room for aggregation in the space of capabilities.
- 3.
The method of scaling assumes perfect substitutability between the functionings: an individual can trade off her welfare in terms of health and education with an infinite elasticity of substitution. Fuzzy sets theory as applied in the empirical capability literature is an extension of the method of scaling. It was pioneered in this area by Chiappero Martinetti (2000) and has been applied by Lelli (2001) and Qizilbash (2002). It extends the method of scaling in two respects. First, it the indicator variable into a 0-1 interval by allowing for nonlinear projection functions such as a sigmoid function. By allowing for different weighting schemes, the use of fuzzy sets provides more flexible substitution patterns between functionings. For example the arithmetic average is sometimes replaced by a Liontief Function (Kuklys 2005) and in this case as the assumed elasticity of substitution between the functionings is zero, no trade-off takes place between functionings.
- 4.
In each state, the rural sample was selected in two stages and in urban areas, a three-stage procedure was followed. In rural areas, with Probability Proportional to Population Size (PPS) at the first stage, Primary Sampling Units (PSUs) were selected. Here census villages are the PSUs. In the second stage, households were randomly selected within each PSU. In urban areas, in the first stage, wards were selected with PPS sampling. At the next stage, one Census Enumeration Block (CEB) was randomly selected from each sample ward. In final stage, households were selected randomly within each selected CEB.
- 5.
PERMISS is contributing negatively towards the attainment of autonomy.
- 6.
Housing condition is a latent variable which is measured in terms of an index constructed by extracting principal component(s) and factor scores from a group of related variables like type of wall material, type of roof material, cooking fuel type, toilet type, source of drinking water, source of lighting, etc. Appendix B
- 7.
Given the nature of available NFHS-3 data, the LISREL programme fails to complete loop for two indicators, viz., CONTRALIT and AUT. Hence, here no regression weight could be obtained and these dimensions are eventually dropped from the relevant sets of functioning.
- 8.
We demonstrated this phenomenon before in our earlier work on a primary data set (Bhattacharya and Banerjee 2012). A critique of the idea of considering autonomy as the sole indicator of empowerment was presented and an attempt was made to supplement autonomy with other dimensions like health and knowledge in shaping empowerment. The results demonstrated the fact that high autonomy along with high attainment in other capabilities definitely improves the empowerment index, but considerable empowerment-attainment may be observed even with low autonomy but with higher achievements in other capabilities and vice versa.
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Appendices
Appendix A
Variable-description
Variable | Description | Categories | Variable Name |
|---|---|---|---|
Observed causes | |||
Age (v012) | Women of age group 15–25 yrs | 1 | AGE |
Women of age group 26–35 yrs | 2 | ||
Women of age group 36–49 yrs | 3 | ||
Religion (v130) | Hindu | 1 | RELGN |
Muslim | 2 | ||
Christ, Buddhist, Sikh, Jain, Others | 3 | ||
Caste (s46) | General | 1 | CASTE |
SC | 2 | ||
ST, OBC, Others, don’t know | 3 | ||
Relationship with head of the household (v150) | Head, wife | 1 | RELNHH |
Daughter, daughter-in-law, sister | 2 | ||
3 | |||
Others | |||
Marital status (v501) | Married | 1 | MSTATUS |
Never Married | 2 | ||
Divorced, Widowed, not living together | 3 | ||
Wealth index (v190) | Poorest, Poorer | 1 | WINDEX |
Middle Income | 2 | ||
Richer, Richest | 3 | ||
Observed causes: Housing condition (HSC) (index constructed) | |||
Drinking water (v113) | Piped into dwelling, piped to yard, public tap, tube well, protected well, unprotected well, river/canal/pond etc., tanker, bottled water, others | ||
Toilet type (v116) | Flush to piped sewer, flush to septic tank, flush to pit, flush to somewhere else, flush, do no’t know where, ventilated improved pit latrine (VIP), pit latrine with slab, pit latrine without slab, no facility, dry toilet, others | ||
Sources of lighting (v119) | Electricity (present/absent) | ||
Cooking fuel type (v161) | Electricity, LPG, biogas, kerosene, coal, charcoal, wood, straw/grass, agricultural crops, animal dung, others | ||
Type of wall material (v128) | No wall, cane/palm/trunks, mud, grass, bamboo with mud, plywood, unburnt brick, reused wood, cement/concrete, stone, burnt brick, cement block, wood planks, gi/metal, others | ||
Type of roof material (vv129) | Mud/clay, sand, dung, raw wood planks, palm/bamboo, brick, stone, vinyl, ceramic tiles, cement, carpet | ||
Indicators for HEALTH | |||
BMI* (v445) | Varies between 12.10 to 20.00 | 1 | BMI |
Varies between 20.00 to 30.00 | 2 | ||
Varies between 30.00 to 48.68 | 3 | ||
Anaemia** (v453) | Varies between 3.3 to 5.00 | 1 | ANAEMIA |
Varies between 5.00 to 10.00 | 2 | ||
Varies between 10.00 to 16.6 | 3 | ||
Food Intake (s558a-g) Consumption of food items (Milk or Card, Pulses or beans, dark green leafy vegetables, fruits, eggs, fish, chicken or meat): | Daily | 1 | INTAKE |
Weekly | 2 | ||
Occasionally, never | 3 | ||
Indicators for Education | |||
Educational achievement (v149) | No education, incomplete primary | 1 | EDU |
Complete primary, incomplete secondary | 2 | ||
Complete secondary, higher | 3 | ||
Ability to read (v155) | Can’t read at all | 1 | FLIT |
Able to read only parts of sentence | 2 | ||
3 | |||
Able to read whole sentence | |||
Knowledge of Contraceptive Method (v301) | Knows no method | 1 | CONTRALIT |
Knows only traditional method | 2 | ||
Knows modern method | 3 | ||
Indicators for Autonomy | |||
Decision taken by (v632, v739, w124, v743a) (How to spend money, contraception use, access to health care facility, money for own use) | Respondent alone | 1 | AUT |
Jointly with husband/partner, other | 2 | ||
Mainly husband/partner | 3 | ||
Domestic violence (d104, d105a-j, d109, d110a-e, d115b-y) (ever pushed shook, throw something, slapped, punched, kicked, dragged, strangled or burn, attacked with knife, gun, forced sex, twisted arm or hair) | No, often during last 12Â months | 1 | PRCVD |
Sometimes during last 12Â months | 2 | ||
Not in last 12Â months, yes, but currently a widow | 3 | ||
Permission Requirement (s824a-c) (market, other household, health facility) | alone | 1 | PERMISS |
With someone else only | 2 | ||
Not at all | 3 | ||
Appendix B
Construction of Housing Condition Index
Principal component analysis method (PCA) has been used to calculate the housing condition index. Here six variables indicating one’s housing condition have been used, viz., drinking water (drwtr), toilet type (toilet), lighting source (litng), fuel use (fuel), wall material (wall) and roof material (roof).
The output is as follows:
KMO and Bartlett’s Test
Kaiser–Meyer–Olkin. | Measure of sampling adequacy | 0.844 |
Bartlett’s test of sphericity | Approx. Chi Square | 14501.688 |
df | 15 | |
Sig. | 0.000 |
Here, the value Kaiser–Meyer–Olkin measure of sampling adequacy is 0.844 which is far beyond the acceptable minimum of 0.6. On the other hand, Bartlett’s test of Sphericity is significant here. Therefore, it is possible to conduct a PCA with the present dataset.
Total Variance Explained
Component | Initial eigen values | Extraction sums of squared loadings | ||||
|---|---|---|---|---|---|---|
Total | % of Variance | Cumulative  % | Total | % of Variance | Cumulative  % | |
1 | 3.201 | 53.354 | 53.354 | 3.201 | 53.354 | 53.354 |
2 | 1.009 | 16.811 | 70.166 | 1.009 | 16.811 | 70.166 |
3 | 0.618 | 10.297 | 80.463 | Â | Â | Â |
4 | 0.424 | 7.063 | 87.526 | Â | Â | Â |
5 | 0.391 | 6.518 | 94.044 | Â | Â | Â |
6 | 0.357 | 5.956 | 100.000 | Â | Â | Â |
Extraction Method Principal Component Analysis.
In the above table, the eigen values which are the variance of the components are available for all six variables. From the result it’s clear that there are two regression factor score for the housing condition index. The weighted average of these two factor score forms the required housing condition index, where weights are 3.201 and 1.009, respectively.
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Bhattacharya, J., Banerjee, S., Bose, M. (2013). On Assessment of Women Empowerment at Individual Level: An Analytical Exposition. In: Banerjee, S., Chakrabarti, A. (eds) Development and Sustainability. Springer, India. https://doi.org/10.1007/978-81-322-1124-2_16
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